# How to Build from Source

Build the Audio Analyzer microservice from source to customize, debug, or extend its functionality. In this guide, you will:
- Set up your development environment.
- Compile the source code and resolve dependencies.
- Generate a runnable build for local testing or deployment.

This guide is ideal for developers who want to work directly with the source code.


# Prerequisites

Before you begin, ensure the following:
- **System Requirements**: Verify your system meets the [minimum requirements](./system-requirements.md).
- This guide assumes basic familiarity with Git commands, Python virtual environments, and terminal usage. If you are new to these concepts, see:
  - [Git Documentation](https://git-scm.com/doc)
  - [Python Virtual Environments](https://docs.python.org/3/tutorial/venv.html)
- Follow all the steps provided in [get started](./get-started.md) documentation with respect to [environment variables](./get-started.md#environment-variables) configuration, setting up of [storage backends](./get-started.md#setup-the-storage-backends) and [model selection](./get-started.md#models-selection).

# Steps to Build

Following options are provided to build the microservice.

- [Build and run application with required dependencies using Docker Script](#build-and-run-using-docker-script).
- [Build and run on host using Setup Script](#setup-and-run-on-host-using-setup-script).

## Build and Run using Docker Script

1. Clone the repository:
    ```bash
    # Clone the latest on mainline
    git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries
    # Alternatively, Clone a specific release branch
    git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries -b <release-tag>
    ```

2. Default storage backend used in the Docker script based setup is `minio`. We need to set following required environment variables for Minio on shell:

    ```bash
    # MinIO credentials (required)
    export MINIO_ACCESS_KEY=<your-minio-username>
    export MINIO_SECRET_KEY=<your-minio-password>
    ```

    > __NOTE :__ To override the default storage backend, see [setup the storage backends](./get-started.md#setup-the-storage-backends).

3. The Docker setup will build the image if not already present on the machine. We can optionally set a registry URL and tag, if we wish to push this image to any repository. If not set, default image will be built as `audio-analyzer:latest`.

    ```bash
    # Optional: Set registry URL and project name for docker image naming
    export REGISTRY_URL=<your-registry-url>
    export PROJECT_NAME=<your-project-name>
    export TAG=<your-tag>
    ```

    If `REGISTRY_URL` is provided, the final image name will be: `${REGISTRY_URL}${PROJECT_NAME}/audio-analyzer:${TAG}`  
    If `REGISTRY_URL` is not provided, the image name will be: `${PROJECT_NAME}/audio-analyzer:${TAG}`

4. Set the required environment variables:

    ```bash
    # (Required) Comma-separated list of models to download
    export ENABLED_WHISPER_MODELS=small.en,tiny.en,medium.en  
    ```

5. **(OPTIONAL)** You can customize the setup with these additional environment variables:

    ```bash
    # Set a default model to use, if one is not provided explicitly. Should be one of the ENABLED_WHISPER_MODELS
    export DEFAULT_WHISPER_MODEL=tiny.en

    # Device to use: cpu, gpu, or auto
    export DEFAULT_DEVICE=cpu
    export USE_FP16=true

    # Storage backend: minio or local
    export STORAGE_BACKEND=minio
    export MAX_FILE_SIZE=314572800
    ```

3. Run the setup script to build and bring up production version of application. This also brings up Minio Server container (if default **minio** storage backend is used):

    ```bash
    cd edge-ai-libraries/microservices/audio-analyzer
    chmod +x ./setup_docker.sh
    ./setup_docker.sh
    ```

### Docker Setup Options

The `setup_docker.sh` script when run without any parameters builds and runs the production docker images. It additionally supports the following options:

```
Options:
  --dev                 Build and run development environment
  --build               Only build production Docker image
  --build-dev           Only build development Docker image  
  --down                Stop and remove all containers, networks, 
                        and volumes  
  -h, --help            Show this help message
```

Examples:
- Production setup: `./setup_docker.sh`
- Development setup: `./setup_docker.sh --dev`
- Build production image only: `./setup_docker.sh --build`
- Build development image only: `./setup_docker.sh --build-dev`
- Stop and remove all containers: `./setup_docker.sh --down`

The development environment provides:
- Hot-reloading of code changes
- Mounting of local code directory into container
- Debug logging enabled

The production environment uses:
- Gunicorn with multiple worker processes
- Optimized container without development dependencies
- No source code mounting (code is copied at build time)

## Setup and run on host using Setup Script

1. Clone the repository:
    ```bash
    # Clone the latest on mainline
    git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries
    # Alternatively, Clone a specific release branch
    git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries -b <release-tag>
    ```

2. Run the setup script with desired options:
    ```bash
    cd edge-ai-libraries/microservices/audio-analyzer
    chmod +x ./setup_host.sh
    ./setup_host.sh
    ```

Available options:
- `--debug`, `-d`: Enable debug mode
- `--reload`, `-r`: Enable auto-reload on code changes

The setup script will:
- Install all required system dependencies
- Create directories for model storage. **For host setup using script, only storage backend available is local filesystem.**
- Install Poetry and project dependencies
- Start the Audio Analyzer service

## Validation

1. **Verify Build Success**:
   - Check the logs. Look for confirmation messages indicating the microservice started successfully.

## Troubleshooting


## Supporting Resources
* [Overview](Overview.md)
* [System Requirements](system-requirements.md)
* [API Reference](api-reference.md)